Full Bayes linear intervention models have been recently proposed to conduct before-after safety studies. These models assume linear slopes to represent the time and treatment effects across the treated and comparison sites. However, the linear slope assumption can only furnish some restricted treatment profiles. To overcome this problem, a first-order autoregressive (AR1) safety performance fu...

Biosensors are of increasing interest for the detection of bacterial pathogens in many applications such as human, animal and plant health, as well as food and water safety. Membranes and membrane-like structures have been integral part of several pathogen detection platforms. Such structures may serve as simple mechanical support, function as a part of the transduction mechanism, may be used t...

Robotics algorithms typically depend on various parameters, the choice of which significantly affects the robot’s performance. While an initial guess for the parameters may be obtained from dynamic models of the robot, parameters are usually tuned manually on the real system to achieve the best performance. Optimization algorithms, such as Bayesian optimization, have been used to automate this ...

this paper presents a deterministic approach for performance assessment of different province’s road safety level at iran. a data envelopment analysis (dea) model considering undesirable input and output indices and a multivariate statistical method, principle component analysis (pca) are used in this paper, while previous studies do not use composite pca-dea method and undesirable input and ou...

This paper is aimed at filling the gap between theory and practice in the area of safety stocks under MRP environments. It is focused on providing a new methodology for dimensioning an overall buffer against uncertainty in market demand, which often plagues SMEs – that act as sub-contractors or suppliers within large projects or they have a reduced bargaining power – and adversely affects their...